Fight gaming fraud with AI and machine learning

Presented by

Jeff Sakasegawa, Trust and Safety Architect, Sift Science

About this talk

Globally there are 2.2 billion active gamers, and 47 percent of them shell out cash while they play. And 100 percent of them are at risk from fraudsters who rip off everything from a gamer’s identity to their credit cards, online goods, and trust in your company. With every instance of fraud, your reputation takes a nose dive, driving away customers and directly impacting your bottom line. But fraud is notoriously difficult to combat. Legacy rules-based approaches have never been able to keep up with fraudsters, who constantly evolve their techniques using sophisticated technology like automated scripts and bots. That’s why machine learning and artificial intelligence are being leveraged to detect fraud before it affects your company and end users. Machine learning can sift through billions of game events and analyze vast streams of data in real time to stop fraud in its tracks. To learn more about how machine learning and AI can keep your game and players safe from increasingly aggressive online criminals, don’t miss this VB Live event! In this webinar, you'll learn: * How the gaming industry can secure gamer data and build trust * How account takeover, fake licensing, spam, and scams pose a particular challenge to gamers and gaming platforms * What policies your company should have in place around data breach ransom * How to combat trolling Speakers: * Jeff Sakasegawa, Trust and Safety Architect, Sift Science * Dean Takahashi, Lead Writer, GamesBeat * Scott Adams, CEO, Former Director of Fraud & Risk, Riot Games * Rachael Brownell, Moderator, VentureBeat Sponsored by Sift Science

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